code: def test_model_func_call_gpu():
      X, y = make_regression(
          n_samples=81,
          n_features=10,
          noise=0.1,
          random_state=42,
          dtype=np.float32,
      )
  
      model = reg().fit(X, y)
  
      z = model_func_call(X=X, model_func=model.predict, gpu_model=True)
  
      assert isinstance(z, cp.ndarray)
  
      z = model_func_call(
          X=cp.asnumpy(X), model_func=dummy_func, gpu_model=False
      )
  
      assert isinstance(z, cp.ndarray)
  
      with pytest.raises(TypeError):
          z = model_func_call(
              X=X, model_func=dummy_func, gpu_model=True
          )
  
      model = PCA(n_components=10).fit(X)
  
      z = model_func_call(
          X=X, model_func=model.transform, gpu_model=True
      )
  
      assert isinstance(z, cp.ndarray)
  
imports: from pylibraft.common.handle import Handle
  from sklearn.linear_model import LinearRegression
  from cuml.datasets import make_regression
  from cuml.testing.utils import ClassEnumerator
  from cuml.explainer.common import model_func_call
  from cuml.explainer.common import link_dict
  from cuml.explainer.common import get_tag_from_model_func
  from cuml.explainer.common import get_link_fn_from_str_or_fn
  from cuml.explainer.common import get_handle_from_cuml_model_func
  from cuml.explainer.common import get_dtype_from_model_func
  from cuml.explainer.common import get_cai_ptr
  from cuml import PCA
  from cuml import LinearRegression
  import pytest
  from cuml.internals.safe_imports import cpu_only_import
  import cuml
  from cuml.internals.safe_imports import gpu_only_import
label_desc: Use image node_id 6 for calling a global function with example usage: test_model_func_call_gpu() without return types